def _getDiagonalElements(self, eigenvalues, twoform_vectors,
distribution_plan):
x_coordinates = twoform_vectors.xCoordinates()
y_coordinates = twoform_vectors.yCoordinates()
diagonal_elements = np.zeros((len(x_coordinates), len(y_coordinates)),
dtype=np.complex128)
print("Determining diagonal elements")
for i_mode in range(distribution_plan.totalShape()[0]):
logAll("Processing mode: %i" % i_mode)
new_mode = twoform_vectors.read(i_mode).coveredInterpolation(
x_coordinates, y_coordinates)
norm_mode = trapez2D(np.abs(new_mode)**2, 1, 1)**0.5
if np.isnan(norm_mode):
print("SKIP:", i_mode, norm_mode)
sys.stdout.flush()
continue
diagonal_elements[:, :] += eigenvalues[i_mode] * np.abs(
new_mode[:, :])**2
#total_diagonal_elements = np.zeros_like(diagonal_elements)
#mpi.COMM_WORLD.Allreduce(diagonal_elements, total_diagonal_elements, op=mpi.SUM)
total_diagonal_elements = diagonal_elements
return total_diagonal_elements, diagonal_elements
def _getDiagonalElements(self, eigenvalues, twoform_vectors, distribution_plan):
x_coordinates = twoform_vectors.xCoordinates()
y_coordinates = twoform_vectors.yCoordinates()
diagonal_elements = np.zeros((len(x_coordinates), len(y_coordinates)),
dtype=np.complex128)
print("Determining diagonal elements")
for i_mode in range(distribution_plan.totalShape()[0]):
logAll("Processing mode: %i" % i_mode)
new_mode = twoform_vectors.read(i_mode).coveredInterpolation(x_coordinates, y_coordinates)
norm_mode = trapez2D( np.abs(new_mode)**2, 1, 1)**0.5
if np.isnan(norm_mode):
print("SKIP:", i_mode,norm_mode)
sys.stdout.flush()
continue
diagonal_elements[:, :] += eigenvalues[i_mode] * np.abs(new_mode[:, :])**2
#total_diagonal_elements = np.zeros_like(diagonal_elements)
#mpi.COMM_WORLD.Allreduce(diagonal_elements, total_diagonal_elements, op=mpi.SUM)
total_diagonal_elements = diagonal_elements
return total_diagonal_elements, diagonal_elements
def propagate_af(self, autocorrelation_function,
directory_name="propagation_wofry",
af_output_file_root=None,
maximum_mode=None, # this is indeed the NUMBER OF MODES (maximum index plus one)
python_to_be_used="/users/srio/OASYS1.1/miniconda3/bin/python"):
propagator = AutocorrelationFunctionPropagator(self)
if maximum_mode is None:
mode_distribution = autocorrelation_function.modeDistribution()
maximum_mode = mode_distribution[abs(mode_distribution) > 0.00005].shape[0]
propagator.setMaximumMode(maximum_mode)
data_directory = "%s/%s" % (directory_name, "wavefronts")
if isMaster():
if not os.path.exists(directory_name):
os.mkdir(directory_name)
if not os.path.exists(data_directory):
os.mkdir(data_directory)
barrier()
# propagated_filename = "%s/%s.npz" % (data_directory, af_name)
propagated_filename = "%s/%s.npz" % (data_directory, "wavefront")
af = propagator.propagate(autocorrelation_function, propagated_filename, method="WOFRY",
python_to_be_used=python_to_be_used)
barrier()
if isMaster():
if af_output_file_root is not None:
af.save("%s.npz" % (af_output_file_root))
logAll("File written to disk: %s.npz" % (af_output_file_root))
return af
def propagateWavefrontWofry(beamline,
wavefront,
i_mode,
python_to_be_used="python",
keep_temp_files=False):
s_id = str(mpi.COMM_WORLD.Get_rank()) + "_" + gethostname()
wavefront.save("./tmp/tmp%s_in" % s_id)
parameter_lines = "s_id=\"%s\"" % (s_id)
pickle.dump(beamline, open("./tmp/tmp%s_beamline.p" % s_id, "wb"))
lines = """
import pickle
from wofry.propagator.propagator import PropagationManager
from wofry.propagator.propagators2D.fresnel_zoom_xy import FresnelZoomXY2D
from comsyl.waveoptics.ComsylWofryBeamline import ComsylWofryBeamline
# initialize propagator
mypropagator = PropagationManager.Instance()
try:
mypropagator.add_propagator(FresnelZoomXY2D())
except:
print("May be you alreay initialized propagator and stored FresnelZoomXY2D")
beamline = pickle.load(open("./tmp/tmp%s_beamline.p"%s_id,"rb"))
ComsylWofryBeamline.propagate_numpy_wavefront(
"./tmp/tmp%s_in.npz"%s_id,
"./tmp/tmp%s_out.npz"%s_id,
beamline,mypropagator)
"""
file = open("./tmp/tmp%s.py" % s_id, "w")
file.writelines(parameter_lines)
file.writelines("\ni_mode=%d\n" % i_mode) # added srio
file.writelines(lines)
file.close()
os.system(python_to_be_used + " ./tmp/tmp%s.py" % s_id)
if keep_temp_files: # keep a copy of all files
logAll("cp %s %s" %
("./tmp/tmp%s_in.npz" % s_id, "./tmp/tmp%s_in_mode%d.npz" %
(s_id, i_mode)))
logAll("cp %s %s" %
("./tmp/tmp%s_out.npz" % s_id, "./tmp/tmp%s_out_mode%d.npz" %
(s_id, i_mode)))
os.system("cp %s %s" %
("./tmp/tmp%s_in.npz" % s_id, "./tmp/tmp%s_in_mode%d.npz" %
(s_id, i_mode)))
os.system("cp %s %s" %
("./tmp/tmp%s_out.npz" % s_id, "./tmp/tmp%s_out_mode%d.npz" %
(s_id, i_mode)))
return NumpyWavefront.load("./tmp/tmp%s_out.npz" % s_id)
def _adjustWavefrontSize(self, wavefront):
min_size_dims = min(wavefront.dim_x(), wavefront.dim_y())
i = 0
max_size = 4096
if min_size_dims > max_size:
j = min_size_dims
while j > max_size:
j /= 2
i += 1
new_size_x = wavefront.dim_x() / 2**i
new_size_y = wavefront.dim_y() / 2**i
if new_size_x != wavefront.dim_x() or new_size_y != wavefront.dim_y():
logAll("Resized to %i %i" % (new_size_x, new_size_y))
return wavefront.asFixedSize(new_size_x, new_size_y)
else:
return wavefront
def propagateWavefrontWofry(beamline, wavefront, i_mode, python_to_be_used="python", keep_temp_files=False):
s_id=str(mpi.COMM_WORLD.Get_rank())+"_"+gethostname()
wavefront.save("./tmp/tmp%s_in"%s_id)
parameter_lines = "s_id=\"%s\"" % (s_id)
pickle.dump(beamline, open("./tmp/tmp%s_beamline.p"%s_id,"wb"))
lines ="""
import pickle
from wofry.propagator.propagator import PropagationManager
from wofry.propagator.propagators2D.fresnel_zoom_xy import FresnelZoomXY2D
from comsyl.waveoptics.ComsylWofryBeamline import ComsylWofryBeamline
# initialize propagator
mypropagator = PropagationManager.Instance()
try:
mypropagator.add_propagator(FresnelZoomXY2D())
except:
print("May be you alreay initialized propagator and stored FresnelZoomXY2D")
beamline = pickle.load(open("./tmp/tmp%s_beamline.p"%s_id,"rb"))
ComsylWofryBeamline.propagate_numpy_wavefront(
"./tmp/tmp%s_in.npz"%s_id,
"./tmp/tmp%s_out.npz"%s_id,
beamline,mypropagator)
"""
file = open("./tmp/tmp%s.py"%s_id, "w")
file.writelines(parameter_lines)
file.writelines("\ni_mode=%d\n"%i_mode) # added srio
file.writelines(lines)
file.close()
os.system(python_to_be_used+" ./tmp/tmp%s.py"%s_id)
if keep_temp_files: # keep a copy of all files
logAll("cp %s %s" % ("./tmp/tmp%s_in.npz" % s_id, "./tmp/tmp%s_in_mode%d.npz" % (s_id, i_mode)))
logAll("cp %s %s" % ("./tmp/tmp%s_out.npz" % s_id, "./tmp/tmp%s_out_mode%d.npz" % (s_id, i_mode)))
os.system("cp %s %s" % ("./tmp/tmp%s_in.npz" % s_id, "./tmp/tmp%s_in_mode%d.npz" % (s_id, i_mode)))
os.system("cp %s %s" % ("./tmp/tmp%s_out.npz" % s_id, "./tmp/tmp%s_out_mode%d.npz" % (s_id, i_mode)))
return NumpyWavefront.load("./tmp/tmp%s_out.npz"%s_id)
def _adjustWavefrontSize(self, wavefront):
min_size_dims = min(wavefront.dim_x(), wavefront.dim_y())
i = 0
max_size = 4096
if min_size_dims > max_size:
j = min_size_dims
while j > max_size:
j /= 2
i += 1
new_size_x = wavefront.dim_x() / 2**i
new_size_y = wavefront.dim_y() / 2**i
if new_size_x != wavefront.dim_x() or new_size_y != wavefront.dim_y():
logAll("Resized to %i %i" %(new_size_x, new_size_y))
return wavefront.asFixedSize(new_size_x, new_size_y)
else:
return wavefront
def propagate_af(
self,
autocorrelation_function,
directory_name="propagation_wofry",
af_output_file_root=None,
maximum_mode=None, # this is indeed the NUMBER OF MODES (maximum index plus one)
python_to_be_used="/users/srio/OASYS1.1/miniconda3/bin/python"):
propagator = AutocorrelationFunctionPropagator(self)
if maximum_mode is None:
mode_distribution = autocorrelation_function.modeDistribution()
maximum_mode = mode_distribution[
abs(mode_distribution) > 0.00005].shape[0]
propagator.setMaximumMode(maximum_mode)
data_directory = "%s/%s" % (directory_name, "wavefronts")
if isMaster():
if not os.path.exists(directory_name):
os.mkdir(directory_name)
if not os.path.exists(data_directory):
os.mkdir(data_directory)
barrier()
# propagated_filename = "%s/%s.npz" % (data_directory, af_name)
propagated_filename = "%s/%s.npz" % (data_directory, "wavefront")
af = propagator.propagate(autocorrelation_function,
propagated_filename,
method="WOFRY",
python_to_be_used=python_to_be_used)
barrier()
if isMaster():
if af_output_file_root is not None:
af.save("%s.npz" % (af_output_file_root))
logAll("File written to disk: %s.npz" % (af_output_file_root))
return af
import mpi4py.MPI as mpi
from comsyl.utils.Logger import logAll, log
from comsyl.parallel.utils import isMaster, barrier
from socket import gethostname
from comsyl.parallel.DistributionPlan import DistributionPlan
import os
if isMaster():
print("Hello from master")
if isMaster():
if not os.path.exists("tmp"):
os.mkdir("tmp")
logAll("Using LogAll")
log("Using Log")
s_id = str(mpi.COMM_WORLD.Get_rank()) + "_" + gethostname()
print("s_id: ", s_id)
print("str(mpi.COMM_WORLD.Get_rank()): ", str(mpi.COMM_WORLD.Get_rank()))
number_modes = 1000
distribution_plan = DistributionPlan(mpi.COMM_WORLD,
n_rows=number_modes,
n_columns=1)
print(distribution_plan)
f = open("./tmp/TMP%s_in" % s_id, 'w')
f.write(">>>>>>>>>")
f.close
def propagate(self,
autocorrelation_function,
filename,
method='SRW',
python_to_be_used="python"):
source_filename = autocorrelation_function._io.fromFile()
try:
source_uid = autocorrelation_function.info().uid()
except:
source_uid = "None"
autocorrelation_function.info().logStart()
logAll("Propagating %s (%s)" % (source_filename, source_uid))
if self._maximum_mode is None:
number_modes = autocorrelation_function.numberModes()
else:
number_modes = self._maximum_mode
if isMaster():
if not os.path.exists("tmp"):
os.mkdir("tmp")
distribution_plan = DistributionPlan(mpi.COMM_WORLD,
n_rows=number_modes,
n_columns=1)
n_rank = mpi.COMM_WORLD.Get_rank()
x_coordinates = []
y_coordinates = []
for i_mode in distribution_plan.localRows():
for i in range(1):
logAll("%i doing mode index: %i/%i (max mode index: %i)" %
(n_rank, i_mode, max(
distribution_plan.localRows()), number_modes - 1))
if n_rank == 0:
sys.stdout.flush()
wavefront = autocorrelation_function.coherentModeAsWavefront(
i_mode)
#wavefront._e_field[np.abs(wavefront._e_field)<0.000001]=0.0
if method == 'SRW':
# CHANGE THIS FOR WOFRY
srw_wavefront = propagateWavefront(
self.__srw_beamline,
wavefront,
autocorrelation_function.SRWWavefrontRx(),
autocorrelation_function.SRWWavefrontDRx(),
autocorrelation_function.SRWWavefrontRy(),
autocorrelation_function.SRWWavefrontDRy(),
1.0,
1.0,
i_mode,
python_to_be_used=python_to_be_used)
elif method == 'WOFRY':
srw_wavefront = propagateWavefrontWofry(
self.__srw_beamline,
wavefront,
i_mode,
python_to_be_used=python_to_be_used)
else:
raise Exception("Method not known: %s" % method)
# norm_mode = trapez2D( np.abs(srw_wavefront.E_field_as_numpy()[0,:,:,0])**2, 1, 1)**0.5
# if norm_mode > 1e2 or np.isnan(norm_mode):
# print("TRY %i AFTER PROPAGATION:" % i, i_mode,norm_mode)
# sys.stdout.flush()
#else:
# break
#if i==19:
# exit()
# if np.any(norm_srw_wavefront > 10):
# exit()
#
# if np.any(norm_wavefront > 10):
# exit()
adjusted_wavefront = self._adjustWavefrontSize(srw_wavefront)
# norm_mode = trapez2D( np.abs(adjusted_wavefront.E_field_as_numpy()[0,:,:,0])**2, 1, 1)**0.5
# if norm_mode > 1e2 or np.isnan(norm_mode):
# print("TRY %i AFTER ADJUSTMENT:" % i, i_mode,norm_mode)
# sys.stdout.flush()
# exit()
# writes a file for every wavefront
TwoformVectorsWavefronts.pushWavefront(filename,
adjusted_wavefront,
index=i_mode)
#print("Saving wavefront %i" % i_mode)
x_coordinates.append(
adjusted_wavefront.absolute_x_coordinates().copy())
y_coordinates.append(
adjusted_wavefront.absolute_y_coordinates().copy())
mpi.COMM_WORLD.barrier()
# replace the wavefronts bu the propagated ones
af = self._saveAutocorrelation(autocorrelation_function, number_modes,
x_coordinates, y_coordinates, filename)
# convert from one file per wavefront to one big array
af.Twoform().convertToTwoformVectorsEigenvectors()
af.info().setEndTime()
filelist = glob.glob(filename + "*")
for f in filelist:
os.remove(f)
return af
def propagate(self, autocorrelation_function, filename, method='SRW', python_to_be_used="python"):
source_filename = autocorrelation_function._io.fromFile()
try:
source_uid = autocorrelation_function.info().uid()
except:
source_uid = "None"
autocorrelation_function.info().logStart()
logAll("Propagating %s (%s)" % (source_filename, source_uid))
if self._maximum_mode is None:
number_modes = autocorrelation_function.numberModes()
else:
number_modes = self._maximum_mode
if isMaster():
if not os.path.exists("tmp"):
os.mkdir("tmp")
distribution_plan = DistributionPlan(mpi.COMM_WORLD, n_rows=number_modes, n_columns=1)
n_rank = mpi.COMM_WORLD.Get_rank()
x_coordinates = []
y_coordinates = []
for i_mode in distribution_plan.localRows():
for i in range(1):
logAll("%i doing mode index: %i/%i (max mode index: %i)" % (n_rank, i_mode, max(distribution_plan.localRows()), number_modes-1))
if n_rank == 0:
sys.stdout.flush()
wavefront = autocorrelation_function.coherentModeAsWavefront(i_mode)
#wavefront._e_field[np.abs(wavefront._e_field)<0.000001]=0.0
if method == 'SRW':
# CHANGE THIS FOR WOFRY
srw_wavefront = propagateWavefront(self.__srw_beamline,
wavefront,
autocorrelation_function.SRWWavefrontRx(),
autocorrelation_function.SRWWavefrontDRx(),
autocorrelation_function.SRWWavefrontRy(),
autocorrelation_function.SRWWavefrontDRy(), 1.0, 1.0, i_mode,
python_to_be_used=python_to_be_used)
elif method == 'WOFRY':
srw_wavefront = propagateWavefrontWofry(self.__srw_beamline,wavefront,i_mode,python_to_be_used=python_to_be_used)
else:
raise Exception("Method not known: %s"%method)
# norm_mode = trapez2D( np.abs(srw_wavefront.E_field_as_numpy()[0,:,:,0])**2, 1, 1)**0.5
# if norm_mode > 1e2 or np.isnan(norm_mode):
# print("TRY %i AFTER PROPAGATION:" % i, i_mode,norm_mode)
# sys.stdout.flush()
#else:
# break
#if i==19:
# exit()
# if np.any(norm_srw_wavefront > 10):
# exit()
#
# if np.any(norm_wavefront > 10):
# exit()
adjusted_wavefront = self._adjustWavefrontSize(srw_wavefront)
# norm_mode = trapez2D( np.abs(adjusted_wavefront.E_field_as_numpy()[0,:,:,0])**2, 1, 1)**0.5
# if norm_mode > 1e2 or np.isnan(norm_mode):
# print("TRY %i AFTER ADJUSTMENT:" % i, i_mode,norm_mode)
# sys.stdout.flush()
# exit()
# writes a file for every wavefront
TwoformVectorsWavefronts.pushWavefront(filename, adjusted_wavefront, index=i_mode)
#print("Saving wavefront %i" % i_mode)
x_coordinates.append(adjusted_wavefront.absolute_x_coordinates().copy())
y_coordinates.append(adjusted_wavefront.absolute_y_coordinates().copy())
mpi.COMM_WORLD.barrier()
# replace the wavefronts bu the propagated ones
af = self._saveAutocorrelation(autocorrelation_function, number_modes, x_coordinates, y_coordinates, filename)
# convert from one file per wavefront to one big array
af.Twoform().convertToTwoformVectorsEigenvectors()
af.info().setEndTime()
filelist = glob.glob(filename+"*")
for f in filelist:
os.remove(f)
return af